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Record W4402619753 · doi:10.1139/facets-2023-0115

Ideal free distributions form across a regulatory boundary in the Northwest Atlantic Fisheries Organization (NAFO) Division 4X and 5Z groundfish fisheries

2024· article· en· W4402619753 on OpenAlexafffundvenue
Daniel T. Enright, Philip G. Comeau, Darren M. Gillis

Bibliographic record

VenueFACETS · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsFisheries and Oceans CanadaBedford Institute of OceanographyUniversity of Manitoba
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsGroundfishFishingFisheryFisheries managementBoundary (topology)PopulationDistribution (mathematics)Maritime boundaryFish <Actinopterygii>GeographyBiologyMathematicsPolitical science

Abstract

fetched live from OpenAlex

We used isodars, developed from the ideal free distribution (IFD), to predict the distribution of fishing effort across regulatory boundaries in the south-western Scotian Shelf’s haddock fishery. Our analysis was focused around the boundary between Northwest Atlantic Fisheries Organization’s Divisions 4X and 5Z. While effort within 4X was related to the standardized catch value and effort experienced along the 4X–5Z boundary, most effort predictions across the boundary were also accurate. Accuracy of these cross-boundary isodars suggests that a high degree of movement across the boundary meets the IFD assumption of free movement and thus, effort on one side of the boundary is related to fishing success on the other side of the boundary. Fisheries management strategies should adopt a broad view that encompasses adjacent regulatory regions to understand where vessels may choose to fish when multiple regulatory regions are accessible. In fisheries where isodars describe effort distributions across a regulatory boundary, the relative abundance of the underlying fish population could be better indicated by effort distribution among regulatory regions than by catch rates.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.240
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes3
Has abstractyes

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